Abstract:
A chip temperature computation method and a chip temperature computation device are provided. The chip temperature computation method includes: computing an upper layer thermal resistance and a lower layer thermal resistance of a chip, computing a total thermal resistance of the chip, and computing a temperature of the chip according to the total thermal resistance.
Abstract:
A structure of a thermoelectric module including at least one substrate, a thermoelectric device and an insulation protection structure is provided. The thermoelectric device is disposed on the substrate. The insulation protection structure surrounds the thermoelectric device. The thermoelectric device includes at least three electrode plates, first type and second type thermoelectric materials and a diffusion barrier structure. First and second electrode plates among the three electrode plates are disposed on the substrate. The first type thermoelectric material is disposed on the first electrode plate. The second type thermoelectric material is disposed on the second electrode plate. A third electrode plate among the three electrode plates is disposed on the first type and second type thermoelectric materials. The diffusion barrier structure is disposed on two terminals of each of the first type and second type thermoelectric materials. A fabrication method of the foregoing thermoelectric module is also provided.
Abstract:
An encapsulation of backside illumination photosensitive device including a circuit sub-mount, a backside illumination photosensitive device, a plurality of conductive terminals, and a heat dissipation structure is provided. The backside illumination photosensitive device includes an interconnection layer and a photosensitive device array, wherein the interconnection layer is located on the circuit sub-mount, and between the photosensitive device array and the circuit sub-mount. The conductive terminals are located between the interconnection layer and the circuit sub-mount to electrically connect the interconnection layer and the circuit sub-mount. The heat dissipation structure is located under the interconnection layer, and the heat dissipation structure and the photosensitive device array are respectively located at two opposite sides of the interconnection layer.
Abstract:
A board defect filtering method is provided. The method includes: receiving a defect list; obtaining a plurality of defect images of a plurality of defect records on the defect list; receiving a circuit layout image; analyzing a defect location of a first defect image of the plurality of defect images according to the circuit layout image; cropping the first defect image to obtain a first cropped defect image according to the defect location; inputting the first cropping defect image to a defect classifying model; and determining whether the first defect image is a qualified product image or not according to an output result of the defect classifying model.
Abstract:
A chip temperature computation method and a chip temperature computation device are provided. The chip temperature computation method includes: computing an upper layer thermal resistance and a lower layer thermal resistance of a chip, computing a total thermal resistance of the chip, and computing a temperature of the chip according to the total thermal resistance.
Abstract:
A measurement method, a measurement apparatus, and a computer program product for measuring a thermoelectric module are provided. A temperature is provided to the thermoelectric module. A current is applied to the thermoelectric module to turn both sides of the thermoelectric module into a hot side and a cold side. The temperature of the hot side is higher than that of the cold side. A terminal voltage of the thermoelectric module, a hot side temperature of the hot side, and a cold side temperature of the cold side are measured at different time points. A thermoelectric relationship between the terminal voltages and differences between the hot side temperatures and the corresponding cold side temperatures is obtained according to the terminal voltages, the hot side temperatures, and the cold side temperatures. At least one first parameter of the thermoelectric module is estimated according to the thermoelectric relationship.
Abstract:
By adding particles of high thermal conductivity and low thermal expansion coefficient into the copper as a composite material and filling with the composite material into the through-via hole, the mismatch of the coefficient of thermal expansion and the stress of the through-silicon via are lowered and the thermal conductivity of the through-silicon via is increased.
Abstract:
A method and an apparatus for equipment anomaly detection are provided. In the method, multiple signals of an equipment during normal operation or appearance images of the equipment when an appearance is not damaged are acquired in advance by using a data acquisition device to train a machine learning model stored in a storage device. A real-time signal of the equipment during a current operation or a current image of the appearance of the equipment is acquired by using the data acquisition device, and input to the trained machine learning model to output a detection result indicating a current operation state of the equipment or a current state of the appearance of the equipment.
Abstract:
A classification device and a classification method based on a neural network are provided. A heterogeneous integration module includes a convolutional layer, a data normalization layer, a connected layer and a classification layer. The convolutional layer generates a first feature map according to a first image data. The data normalization layer normalizes a first numerical data to generate a first normalized numerical data. The first numerical data corresponds to the first image data. The connected layer generates a first feature vector according to the first feature map and the first normalized numerical data. The classification layer generates a first classification result corresponding to a first time point according to the first feature vector. The heterogeneous integration module generates a second classification result corresponding to a second time point. A recurrent neural network generates a third classification result according to the first classification result and the second classification result.
Abstract:
Provided is a roller with pressure sensor. The roller includes a pressure sensor mounted to the roller. The pressure sensor includes a plurality of pressure sensing units distributed on a thin film. The pressure sensing units are electrically connected to each other with a metal wire but not in contact with each other. Also provided is a roll-to-roll device, which includes a roller mechanism and a pressure sensor.